scholarly journals Local climate impacts of dipole-like sea surface temperature oscillations in the Southern Hemisphere

2020 ◽  
Author(s):  
Jeseung Oh ◽  
Yong Jung
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Hemisphere ◽  
Climate Impacts ◽  
Empirical Orthogonal Functions ◽  
Sea Surface ◽  
Dipole Mode ◽  
Atmospheric Variability ◽  
Cross Correlation Analysis

Abstract Dipole phenomena in ocean-atmospheric variability such as the Indian Ocean Dipole have been recognized as important factors that greatly affect local climates. This study presents evidence of two dipole modes in sea surface temperature anomaly (SSTA) over high latitude Southern Hemisphere (one in South Pacific and one in South Indian Ocean), identified using empirical orthogonal functions and cross-correlation analysis. These dipole modes have interannual periodicity, which is also explored for their seasonal variability and modes. Herein, a dipole mode is defined as a quasi-periodic oscillation between positive and negative phases in the various climate proxies, though predominantly in SST, which is supported by the signal's synchronized relationship with atmospheric variability (as recorded by pressure and wind records). In addition, the dipole modes have a clear synchronization relationship to local precipitation records, which is described in this paper. For this purpose, an index to represent the time-dependent evolution of each dipole mode and to better define and understand the teleconnections of the dipole modes with other climate variables was defined. The findings described here provide a more precise and unique understanding of the globally distributed SSTA teleconnections and climate's synchronized dynamics than that has currently been studied.

scholarly journals ANALYZING THE EFFECT OF INDIAN OCEAN DIPOLE PHENOMENON TO THE ANOMALIES DISTRIBUTION OF SEA SURFACE TEMPERATURE IN WEST SUMATERA

2020 ◽  
Vol 3 (3) ◽  
pp. 260-270
Author(s):  
Nabila Afifah Azuga ◽  
Musrifin Galib ◽  
Elizal
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Indian Ocean Dipole ◽  
Rainfall Intensity ◽  
Sea Surface ◽  
Dipole Mode ◽  
The West ◽  
Sst Anomaly ◽  
Data Processing Methods

The waters of West Sumatera that face directly into Indian Ocean is strongly influenced by Indian Ocean Dipole (IOD) phenomenon which caused an anomaly of sea surface temperature (SST) and affect rainfall intensity in the West Sumatera Province. This research was aimed to know the effect of IOD on the distribution and anomaly of SST and rainfall intensity in West Sumatera. Data processing methods in this research is using statistical and descriptive. The data used in this research are NOAA OI-SST, Dipole Mode Index (DMI), and rainfall data from BKMG. The results showed that IOD positive occured in October 2018 and the IOD negative occured in July 2016. During the positive IOD, SST distribution values were 28 ˚C – 28,8 ˚C and SST anomaly values were ​​-1,2 to -0,4, in the negative phase the distribution of SST values were 29,8 ˚C – 30,35 ˚C and the SST anomaly values were 0,15 to 0,7. The rainfall intensity during positive IOD phase is 157 mm/month and during negative IOD phase is 525 mm/month.

The Contribution of Indian Ocean Sea Surface Temperature Anomalies on Australian Summer Rainfall during El Niño Events

2011 ◽  
Vol 24 (14) ◽  
pp. 3734-3747 ◽  
Author(s):  
Andréa S. Taschetto ◽  
Alex Sen Gupta ◽  
Harry H. Hendon ◽  
Caroline C. Ummenhofer ◽  
Matthew H. England
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Atmospheric Circulation ◽  
Southern Hemisphere ◽  
El Niño ◽  
El Nino ◽  
Sea Surface ◽  
El Niño Events ◽  
The Indian Ocean

Abstract This study investigates the impact of Indian Ocean sea surface temperature (SST) anomalies on the atmospheric circulation of the Southern Hemisphere during El Niño events, with a focus on Australian climate. During El Niño episodes, the tropical Indian Ocean exhibits two types of SST response: a uniform “basinwide warming” and a dipole mode—the Indian Ocean dipole (IOD). While the impacts of the IOD on climate have been extensively studied, the effects of the basinwide warming, particularly in the Southern Hemisphere, have received less attention. The interannual basinwide warming response has important implications for Southern Hemisphere atmospheric circulation because 1) it accounts for a greater portion of the Indian Ocean monthly SST variance than the IOD pattern and 2) its maximum amplitude occurs during austral summer to early autumn, when large parts of Australia, South America, and Africa experience their monsoon. Using observations and numerical experiments with an atmospheric general circulation model forced with historical SST from 1949 to 2005 over different tropical domains, the authors show that the basinwide warming leads to a Gill–Matsuno-type response that reinforces the anomalies caused by changes in the Pacific as part of El Niño. In particular, the basinwide warming drives strong subsidence over Australia, prolonging the dry conditions during January–March, when El Niño–related SST starts to decay. In addition to the anomalous circulation in the tropics, the basinwide warming excites a pair of barotropic anomalies in the Indian Ocean extratropics that induces an anomalous anticyclone in the Great Australian Bight.

scholarly journals On the Angola Low Interannual Variability and Its Role in Modulating ENSO Effects in Southern Africa

2019 ◽  
Vol 32 (15) ◽  
pp. 4783-4803 ◽  
Author(s):  
Salvatore Pascale ◽  
Benjamin Pohl ◽  
Sarah B. Kapnick ◽  
Honghai Zhang
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Africa ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Atmospheric Variability ◽  
Coupled Modes ◽  
Temperature Anomalies ◽  
Sea Surface Temperature Anomalies

Abstract The Angola low is a summertime low pressure system that affects the convergence of low-level moisture fluxes into southern Africa. Interannual variations of the Angola low reduce the seasonal prediction skills for this region that arise from coupled atmosphere–ocean variability. Despite its importance, the interannual dynamics of the Angola low, and its relationship with El Niño–Southern Oscillation (ENSO) and other coupled modes of variability, are still poorly understood, mostly because of the scarcity of atmospheric data and short-term duration of atmospheric reanalyses in the region. To bypass this issue, we use a long-term (3500 year) run from a 50-km-resolution global coupled model capable of simulating the summertime southern African large-scale circulation and teleconnections. We find that the meridional displacement and strength of the Angola low are moderately modulated by local sea surface temperature anomalies, especially those in proximity of the southeastern African coast, and to a lesser extent by ENSO and the subtropical Indian Ocean dipole. Comparison of the coupled run with a 1000-yr run driven by climatological sea surface temperatures reveals that the interannual excursions of the Angola low are in both cases associated with geopotential height anomalies over the southern Atlantic and Indian Ocean related to extratropical atmospheric variability. Midlatitude atmospheric variability explains almost 60% of the variance of the Angola low variability in the uncoupled run, but only 20% in the coupled run. Therefore, while the Angola low appears to be intrinsically controlled by atmospheric extratropical variability, the interference of the atmospheric response forced by sea surface temperature anomalies weakens this influence.

scholarly journals The Influence of Indian Ocean Dipole on Production of Tembang Fishing (Sardinella fimbriata) at Sunda Strait Indonesia

2020 ◽  
pp. 51-58
Author(s):  
Delima Mentari Amara ◽  
Yuniar Mulyani ◽  
Alexander M. A. Khan ◽  
Herman Hamdani
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Indian Ocean Dipole ◽  
Pelagic Fish ◽  
Sea Surface ◽  
Dipole Mode ◽  
Dipole Mode Index ◽  
Mode Index ◽  
The Indian Ocean

Tembang is a pelagic fish which is important in Indonesia and the development on the Sunda Strait. The Indian Ocean Dipole could affect oceanography and at the same time will affect the population of fishes. The aim of this study was to determine the effect of IOD and oceanographic factors on the catch of Tembang fish. This research was conducted in the Sunda Strait waters by looking at the Dipole Mode Index (DMI) and oceanographic ocean conditions such as sea surface temperature and chlorophyll as well as the production of fish catches for 11 years from 2008-2018. IOD affects the catch of Tembang fish by 35.8%. Temperature influences the catch of Tembang fish in the Sunda Strait by 9.48%. Klorofil-a influences the catch of Tembang fish in Sunda Strait by 38.6%. DMI, Temperature, and Chlorophyll affect fish catches by 26.9%.

scholarly journals Interannual Variability of Sea Surface Temperature off Java and Sumatra in a Global GCM*

2008 ◽  
Vol 21 (11) ◽  
pp. 2451-2465 ◽  
Author(s):  
Yan Du ◽  
Tangdong Qu ◽  
Gary Meyers
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Heat Budget ◽  
Sea Surface ◽  
Surface Mixed Layer ◽  
Horizontal Advection ◽  
Cold Anomaly ◽  
Sst Anomalies

Abstract Using results from the Simple Ocean Data Assimilation (SODA), this study assesses the mixed layer heat budget to identify the mechanisms that control the interannual variation of sea surface temperature (SST) off Java and Sumatra. The analysis indicates that during the positive Indian Ocean Dipole (IOD) years, cold SST anomalies are phase locked with the season cycle. They may exceed −3°C near the coast of Sumatra and extend as far westward as 80°E along the equator. The depth of the thermocline has a prominent influence on the generation and maintenance of SST anomalies. In the normal years, cooling by upwelling–entrainment is largely counterbalanced by warming due to horizontal advection. In the cooling episode of IOD events, coastal upwelling–entrainment is enhanced, and as a result of mixed layer shoaling, the barrier layer no longer exists, so that the effect of upwelling–entrainment can easily reach the surface mixed layer. Horizontal advection spreads the cold anomaly to the interior tropical Indian Ocean. Near the coast of Java, the northern branch of an anomalous anticyclonic circulation spreads the cold anomaly to the west near the equator. Both the anomalous advection and the enhanced, wind-driven upwelling generate the cold SST anomaly of the positive IOD. At the end of the cooling episode, the enhanced surface thermal forcing overbalances the cooling effect by upwelling/entrainment, and leads to a warming in SST off Java and Sumatra.

scholarly journals Basin-Scale Prediction of Sea Surface Temperature with Artificial Neural Networks

2018 ◽  
Vol 35 (7) ◽  
pp. 1441-1455 ◽  
Author(s):  
Kalpesh Patil ◽  
M. C. Deo
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Prediction Skill ◽  
Basin Scale ◽  
Ann Models ◽  
Artificial Neural

AbstractThe prediction of sea surface temperature (SST) on the basis of artificial neural networks (ANNs) can be viewed as complementary to numerical SST predictions, and it has fairly sustained in the recent past. However, one of its limitations is that such ANNs are site specific and do not provide simultaneous spatial information similar to the numerical schemes. In this work we have addressed this issue by presenting basin-scale SST predictions based on the operation of a very large number of individual ANNs simultaneously. The study area belongs to the basin of the tropical Indian Ocean (TIO) having coordinates of 30°N–30°S, 30°–120°E. The network training and testing are done on the basis of HadISST data of the past 140 yr. Monthly SST anomalies are predicted at 3813 nodes in the basin and over nine time steps into the future with more than 20 million ANN models. The network testing indicated that the prediction skill of ANNs is attractive up to certain lead times depending on the subbasin. The ANN models performed well over both the western Indian Ocean (WIO) and eastern Indian Ocean (EIO) regions up to 5 and 4 months lead time, respectively, as judged by the error statistics of the correlation coefficient and the normalized root-mean-square error. The prediction skill of the ANN models for the TIO region is found to be better than the physics-based coupled atmosphere–ocean models. It is also observed that the ANNs are capable of providing an advanced warning of the Indian Ocean dipole as well as abnormal basin warming.

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